干旱气象 ›› 2023, Vol. 41 ›› Issue (2): 241-250.DOI: 10.11755/j.issn.1006-7639(2023)-02-0241

• 论文 • 上一篇    下一篇

1997—2021年四川省干旱时空变化特征分析

蔡怡亨1,2(), 李帅3(), 张强4, 邓彪1,2, 罗玉1,2, 孙蕊1,2   

  1. 1.中国气象局成都高原气象研究所/高原与盆地暴雨旱涝灾害四川省重点实验室,四川 成都 610072
    2.四川省气候中心,四川 成都 610072
    3.中国长江三峡集团有限公司流域枢纽运行管理中心 湖北 宜昌 443133
    4.国家气候中心,北京 100081
  • 收稿日期:2022-11-30 修回日期:2023-01-17 出版日期:2023-04-30 发布日期:2023-05-09
  • 通讯作者: 李帅(1987—),男,高级工程师,主要从事水文水资源管理和研究。E-mail:li_shuai@ctg.com.cn
  • 作者简介:蔡怡亨(1995—),男,助理工程师,主要从事气候与气候变化研究。E-mail:1952943140@qq.com
  • 基金资助:
    中国长江三峡集团有限公司项目(0704182);国家自然科学基金项目(52109024);国家重点研发计划项目(2017YFC1502402);甘肃省自然科学基金项目(20JR10RA447)

Spatio-temporal variation of drought in Sichuan Province from 1997 to 2021

CAI Yiheng1,2(), LI Shuai3(), ZHANG Qiang4, DENG Biao1,2, LUO Yu1,2, SUN Rui1,2   

  1. 1. Institute of Plateau Meteorology, CMA/ Heavy Rain and Drought-Flood Disasters in Plateau and Basin Key Laboratory of Sichuan Province, Chengdu 610072, China
    2. Sichuan Provincial Climate Centre, Chengdu 610072, China
    3. Operation and Administration Center for River Basin Hydro Complex, China Three Gorges Corporation, Yichang 443133, Hubei, China
    4. National Climate Centre, Beijing 100081, China
  • Received:2022-11-30 Revised:2023-01-17 Online:2023-04-30 Published:2023-05-09

摘要:

构建适宜的气象干旱指标是开展干旱监测和干旱评价业务服务的基础。基于1997—2021年四川省155个国家气象站逐日平均气温和降水,以及各县(市、区)农作物播种面积资料,通过改进气象干旱综合指数(Meteorological Drought Composite Index, MCI)中的季节调节系数,形成改进的气象干旱综合指数(Modified Meteorological Drought Composite Index, MCIm);再结合历年干旱受灾面积、有效灌溉面积修订区域性干旱过程识别方法,并识别出四川省历年区域性干旱过程51次,然后再利用经验正交函数(Empirical Orthogonal Function,EOF)、旋转经验正交函数(Rotated Empirical Orthogonal Function)、Morlet小波分析法,分析区域性干旱过程时空分布特征。结果表明:1997—2021年四川省发生区域性干旱过程的持续日数呈现出“先变短再增长再变短”,平均影响范围呈现出“先减小再增大再减小”,平均强度和综合强度呈现出“先减弱再增强再减弱”的变化趋势。平均年干旱过程累积日数总体呈现盆地多于盆周山区、盆周山区多于川西高原和攀西地区的特征。年累积MCIm距平EOF分解空间型存在全区一致特征,同时也存在南北反位相特征。四川省可划分为6个区域性干旱气候区,2009—2015年各区年累积MCIm周期变化比2001—2008年更明显。改进后的区域性干旱过程识别方法识别出的干旱过程与干旱灾情更为吻合,更能准确反映四川省干旱发生的实际状况。

关键词: 区域性干旱, 识别, 干旱评估, 改进MCI, 四川省

Abstract:

Constructing suitable meteorological drought indicators is an important foundation for drought monitoring and drought evaluation services. Based on the daily average temperature and precipitation of 155 national meteorological stations in Sichuan Province from 1997 to 2021, as well as the crop area data of each county (city or district), the modified meteorological drought composite index (MCIm) is formed by improving the seasonal adjustment coefficient of the meteorological drought composite index (MCI). The regional drought process identification method was revised according to annual drought disaster area and annual effective irrigation area and 51 regional drought processes in Sichuan Province were identified in the past years. The temporal and spatial distribution characteristics of regional drought processes in Sichuan Province were analyzed by using empirical orthogonal function (EOF), rotated empirical orthogonal function (REOF) and Morlet wavelet analysis. The results show that the evolution results of the durative day, average intensity, average impact area and comprehensive intensity index of the regional drought processes in Sichuan Province decrease initially, followed by increase, but then again decrease. The average annual cumulative days of regional drought process in the basin area were more than those in the mountains area around the basin, and those in the mountains area around the basin were more than those in western Sichuan Plateau and Panxi area. The spatial pattern of annual accumulated MCIm anomaly decomposed by EOF was consistent in Sichuan Province and was also opposite in the northern and southern parts of Sichuan. Sichuan Province can be divided into six drought climatic areas. The annual cumulative MCIm periodic change from 2009 to 2015 was more obvious than that from 2001 to 2008 in each area. The identified regional drought processes according to improved regional drought process identification method are in good agreement with the drought disaster situation and could better reflect the actual situation of drought in Sichuan Province more accurately.

Key words: regional drought, identification, drought assessment, modified meteorological drought composite index, Sichuan Province

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